GigaByte (Hong Kong, China)最新文献_第5页

An improved chromosome-level genome assembly of perennial ryegrass (Lolium perenne L.). 改进的多年生黑麦草（Lolium perenne L.）染色体组水平基因组组装。

GigaByte (Hong Kong, China) Pub Date : 2024-03-06 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.112

Yutang Chen, Roland Kölliker, Martin Mascher, Dario Copetti, Axel Himmelbach, Nils Stein, Bruno Studer

{"title":"An improved chromosome-level genome assembly of perennial ryegrass (Lolium perenne L.).","authors":"Yutang Chen, Roland Kölliker, Martin Mascher, Dario Copetti, Axel Himmelbach, Nils Stein, Bruno Studer","doi":"10.46471/gigabyte.112","DOIUrl":"10.46471/gigabyte.112","url":null,"abstract":"This work is an update and extension of the previously published article \"Ultralong Oxford Nanopore Reads Enable the Development of a Reference-Grade Perennial Ryegrass Genome Assembly\" by Frei et al. The published genome assembly of the doubled haploid perennial ryegrass (Lolium perenne L.) genotype Kyuss (Kyuss v1.0) marked a milestone for forage grass research and breeding. However, order and orientation errors may exist in the pseudo-chromosomes of Kyuss, since barley (Hordeum vulgare L.), which diverged 30 million years ago from perennial ryegrass, was used as the reference to scaffold Kyuss. To correct for structural errors possibly present in the published Kyuss assembly, we de novo assembled the genome again and generated 50-fold coverage high-throughput chromosome conformation capture (Hi-C) data to assist pseudo-chromosome construction. The resulting new chromosome-level assembly Kyuss v2.0 showed improved quality with high contiguity (contig N50 = 120 Mb), high completeness (total BUSCO score = 99%), high base-level accuracy (QV = 50), and correct pseudo-chromosome structure (validated by Hi-C contact map). This new assembly will serve as a better reference genome for Lolium spp. and greatly benefit the forage and turf grass research community.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte112"},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10940895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140144688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Citizen science data on urban forageable plants: a case study in Brazil. 关于城市可食用植物的公民科学数据：巴西案例研究。

GigaByte (Hong Kong, China) Pub Date : 2024-02-21 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.107

Filipi Miranda Soares, Luís Ferreira Pires, Maria Carolina Garcia, Lidio Coradin, Natalia Pirani Ghilardi-Lopes, Rubens Rangel Silva, Aline Martins de Carvalho, Anand Gavai, Yamine Bouzembrak, Benildes Coura Moreira Dos Santos Maculan, Sheina Koffler, Uiara Bandineli Montedo, Debora Pignatari Drucker, Raquel Santiago, Maria Clara Peres de Carvalho, Ana Carolina da Silva Lima, Hillary Dandara Elias Gabriel, Stephanie Gabriele Mendonça de França, Karoline Reis de Almeida, Bárbara Junqueira Dos Santos, Antonio Mauro Saraiva

{"title":"Citizen science data on urban forageable plants: a case study in Brazil.","authors":"Filipi Miranda Soares, Luís Ferreira Pires, Maria Carolina Garcia, Lidio Coradin, Natalia Pirani Ghilardi-Lopes, Rubens Rangel Silva, Aline Martins de Carvalho, Anand Gavai, Yamine Bouzembrak, Benildes Coura Moreira Dos Santos Maculan, Sheina Koffler, Uiara Bandineli Montedo, Debora Pignatari Drucker, Raquel Santiago, Maria Clara Peres de Carvalho, Ana Carolina da Silva Lima, Hillary Dandara Elias Gabriel, Stephanie Gabriele Mendonça de França, Karoline Reis de Almeida, Bárbara Junqueira Dos Santos, Antonio Mauro Saraiva","doi":"10.46471/gigabyte.107","DOIUrl":"10.46471/gigabyte.107","url":null,"abstract":"This paper presents two key data sets derived from the Pomar Urbano project. The first data set is a comprehensive catalog of edible fruit-bearing plant species, native or introduced to Brazil. The second data set, sourced from the iNaturalist platform, tracks the distribution and monitoring of these plants within urban landscapes across Brazil. The study includes data from the capitals of all 27 federative units of Brazil, focusing on the ten cities that contributed the most observations as of August 2023. The research emphasizes the significance of citizen science in urban biodiversity monitoring and its potential to contribute to various fields, including food and nutrition, creative industry, study of plant phenology, and machine learning applications. We expect the data sets presented in this paper to serve as resources for further studies in urban foraging, food security, cultural ecosystem services, and environmental sustainability.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte107"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel variable neighborhood search approach for cell clustering for spatial transcriptomics. 用于空间转录组学细胞聚类的新型变量邻域搜索法

GigaByte (Hong Kong, China) Pub Date : 2024-02-20 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.109

Aleksandra Djordjevic, Junhua Li, Shuangsang Fang, Lei Cao, Marija Ivanovic

引用次数: 0

BatchEval Pipeline: batch effect evaluation workflow for multiple datasets joint analysis. BatchEval Pipeline：用于多个数据集联合分析的批量效应评估工作流程。

GigaByte (Hong Kong, China) Pub Date : 2024-02-20 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.108

Chao Zhang, Qiang Kang, Mei Li, Hongqing Xie, Shuangsang Fang, Xun Xu

{"title":"BatchEval Pipeline: batch effect evaluation workflow for multiple datasets joint analysis.","authors":"Chao Zhang, Qiang Kang, Mei Li, Hongqing Xie, Shuangsang Fang, Xun Xu","doi":"10.46471/gigabyte.108","DOIUrl":"10.46471/gigabyte.108","url":null,"abstract":"As genomic sequencing technology continues to advance, it becomes increasingly important to perform joint analyses of multiple datasets of transcriptomics. However, batch effect presents challenges for dataset integration, such as sequencing data measured on different platforms, and datasets collected at different times. Here, we report the development of BatchEval Pipeline, a batch effect workflow used to evaluate batch effect on dataset integration. The BatchEval Pipeline generates a comprehensive report, which consists of a series of HTML pages for assessment findings, including a main page, a raw dataset evaluation page, and several built-in methods evaluation pages. The main page exhibits basic information of the integrated datasets, a comprehensive score of batch effect, and the most recommended method for removing batch effect from the current datasets. The remaining pages exhibit evaluation details for the raw dataset, and evaluation results from the built-in batch effect removal methods after removing batch effect. This comprehensive report enables researchers to accurately identify and remove batch effects, resulting in more reliable and meaningful biological insights from integrated datasets. In summary, the BatchEval Pipeline represents a significant advancement in batch effect evaluation, and is a valuable tool to improve the accuracy and reliability of the experimental results.Availability & implementation: The source code of the BatchEval Pipeline is available at https://github.com/STOmics/BatchEval.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte108"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generating single-cell gene expression profiles for high-resolution spatial transcriptomics based on cell boundary images. 基于细胞边界图像生成高分辨率空间转录组学的单细胞基因表达谱。

GigaByte (Hong Kong, China) Pub Date : 2024-02-20 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.110

Bohan Zhang, Mei Li, Qiang Kang, Zhonghan Deng, Hua Qin, Kui Su, Xiuwen Feng, Lichuan Chen, Huanlin Liu, Shuangsang Fang, Yong Zhang, Yuxiang Li, Susanne Brix, Xun Xu

{"title":"Generating single-cell gene expression profiles for high-resolution spatial transcriptomics based on cell boundary images.","authors":"Bohan Zhang, Mei Li, Qiang Kang, Zhonghan Deng, Hua Qin, Kui Su, Xiuwen Feng, Lichuan Chen, Huanlin Liu, Shuangsang Fang, Yong Zhang, Yuxiang Li, Susanne Brix, Xun Xu","doi":"10.46471/gigabyte.110","DOIUrl":"10.46471/gigabyte.110","url":null,"abstract":"In spatially resolved transcriptomics, Stereo-seq facilitates the analysis of large tissues at the single-cell level, offering subcellular resolution and centimeter-level field-of-view. Our previous work on StereoCell introduced a one-stop software using cell nuclei staining images and statistical methods to generate high-confidence single-cell spatial gene expression profiles for Stereo-seq data. With advancements allowing the acquisition of cell boundary information, such as cell membrane/wall staining images, we updated our software to a new version, STCellbin. Using cell nuclei staining images, STCellbin aligns cell membrane/wall staining images with spatial gene expression maps. Advanced cell segmentation ensures the detection of accurate cell boundaries, leading to more reliable single-cell spatial gene expression profiles. We verified that STCellbin can be applied to mouse liver (cell membranes) and Arabidopsis seed (cell walls) datasets, outperforming other methods. The improved capability of capturing single-cell gene expression profiles results in a deeper understanding of the contribution of single-cell phenotypes to tissue biology.Availability & implementation: The source code of STCellbin is available at https://github.com/STOmics/STCellbin.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte110"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics. SAW：立体测序空间转录组学高效准确的数据分析工作流程。

GigaByte (Hong Kong, China) Pub Date : 2024-02-20 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.111

Chun Gong, Shengkang Li, Leying Wang, Fuxiang Zhao, Shuangsang Fang, Dong Yuan, Zijian Zhao, Qiqi He, Mei Li, Weiqing Liu, Zhaoxun Li, Hongqing Xie, Sha Liao, Ao Chen, Yong Zhang, Yuxiang Li, Xun Xu

{"title":"SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics.","authors":"Chun Gong, Shengkang Li, Leying Wang, Fuxiang Zhao, Shuangsang Fang, Dong Yuan, Zijian Zhao, Qiqi He, Mei Li, Weiqing Liu, Zhaoxun Li, Hongqing Xie, Sha Liao, Ao Chen, Yong Zhang, Yuxiang Li, Xun Xu","doi":"10.46471/gigabyte.111","DOIUrl":"10.46471/gigabyte.111","url":null,"abstract":"The basic analysis steps of spatial transcriptomics require obtaining gene expression information from both space and cells. The existing tools for these analyses incur performance issues when dealing with large datasets. These issues involve computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the analysis. Here, a high-performance and accurate spatial transcriptomics data analysis workflow, called Stereo-seq Analysis Workflow (SAW), was developed for the Stereo-seq technology developed at BGI. SAW includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation, and clustering. The workflow outputs files in a universal format for subsequent personalized analysis. The execution time for the entire analysis is ∼148 min with 1 GB reads 1 × 1 cm chip test data, 1.8 times faster than with an unoptimized workflow.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte111"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10905255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The genome assembly and annotation of the white-lipped tree pit viper Trimeresurus albolabris. 白唇树蝮的基因组组装和注释。

GigaByte (Hong Kong, China) Pub Date : 2024-01-25 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.106

Xiaotong Niu, Yakui Lv, Jin Chen, Yueheng Feng, Yilin Cui, Haorong Lu, Hui Liu

引用次数: 0

Near chromosome-level and highly repetitive genome assembly of the snake pipefish Entelurus aequoreus (Syngnathiformes: Syngnathidae). 蛇琵琶鱼 Entelurus aequoreus (Syngnathiformes: Syngnathidae) 的近染色体水平和高度重复基因组组装。

GigaByte (Hong Kong, China) Pub Date : 2024-01-11 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.105

Magnus Wolf, Bruno Lopes da Silva Ferrette, Raphael T F Coimbra, Menno de Jong, Marcel Nebenführ, David Prochotta, Yannis Schöneberg, Konstantin Zapf, Jessica Rosenbaum, Hannah A Mc Intyre, Julia Maier, Clara C S de Souza, Lucas M Gehlhaar, Melina J Werner, Henrik Oechler, Marie Wittekind, Moritz Sonnewald, Maria A Nilsson, Axel Janke, Sven Winter

{"title":"Near chromosome-level and highly repetitive genome assembly of the snake pipefish Entelurus aequoreus (Syngnathiformes: Syngnathidae).","authors":"Magnus Wolf, Bruno Lopes da Silva Ferrette, Raphael T F Coimbra, Menno de Jong, Marcel Nebenführ, David Prochotta, Yannis Schöneberg, Konstantin Zapf, Jessica Rosenbaum, Hannah A Mc Intyre, Julia Maier, Clara C S de Souza, Lucas M Gehlhaar, Melina J Werner, Henrik Oechler, Marie Wittekind, Moritz Sonnewald, Maria A Nilsson, Axel Janke, Sven Winter","doi":"10.46471/gigabyte.105","DOIUrl":"10.46471/gigabyte.105","url":null,"abstract":"The snake pipefish, Entelurus aequoreus (Linnaeus, 1758), is a northern Atlantic fish inhabiting open seagrass environments that recently expanded its distribution range. Here, we present a highly contiguous, near chromosome-scale genome of E. aequoreus. The final assembly spans 1.6 Gbp in 7,391 scaffolds, with a scaffold N50 of 62.3 Mbp and L50 of 12. The 28 largest scaffolds (>21 Mbp) span 89.7% of the assembly length. A BUSCO completeness score of 94.1% and a mapping rate above 98% suggest a high assembly completeness. Repetitive elements cover 74.93% of the genome, one of the highest proportions identified in vertebrates. Our demographic modeling identified a peak in population size during the last interglacial period, suggesting the species might benefit from warmer water conditions. Our updated snake pipefish assembly is essential for future analyses of the morphological and molecular changes unique to the Syngnathidae.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte105"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10795108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139492894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Species composition and distribution of the Anopheles gambiae complex circulating in Kinshasa. 金沙萨地区冈比亚按蚊的种类组成和分布。

GigaByte (Hong Kong, China) Pub Date : 2024-01-03 eCollection Date: 2024-01-01 DOI: 10.46471/gigabyte.104

Josue Zanga, Emery Metelo, Nono Mvuama, Victoire Nsabatien, Vanessa Mvudi, Degani Banzulu, Osée Mansiangi, Maxwel Bamba, Narcisse Basosila, Rodrigue Agossa, Roger Wumba

{"title":"Species composition and distribution of the Anopheles gambiae complex circulating in Kinshasa.","authors":"Josue Zanga, Emery Metelo, Nono Mvuama, Victoire Nsabatien, Vanessa Mvudi, Degani Banzulu, Osée Mansiangi, Maxwel Bamba, Narcisse Basosila, Rodrigue Agossa, Roger Wumba","doi":"10.46471/gigabyte.104","DOIUrl":"10.46471/gigabyte.104","url":null,"abstract":"Understanding the distribution of Anopheles species is essential for planning and implementing malaria control programmes. This study assessed the composition and distribution of cryptic species of the main malaria vector, the Anopheles gambiae complex, in different districts of Kinshasa. Anopheles were sampled using CDC light traps in the four Kinshasa districts between July 2021 and June 2022, and then morphologically identified. Equal proportions of Anopheles gambiae s.l. per site were subjected to polymerase chain reaction to identify the cryptic species of the Anopheles gambiae complex. Anopheles gambiae complex specimens were identified throughout Kinshasa. The average density significantly differed inside and outside households. Two species of this complex circulate in Kinshasa: Anopheles gambiae and Anopheles coluzzii. In all the study sites, Anopheles gambiae was the most widespread species. Our results provide an important basis for future studies on the ecology and dynamics of cryptic species of the Anopheles gambiae complex in Kinshasa.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2024 ","pages":"gigabyte104"},"PeriodicalIF":0.0,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10777374/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139426145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities. 纳米孔适应性采样可富集微生物群落中的抗菌药耐药性基因。

GigaByte (Hong Kong, China) Pub Date : 2023-12-11 eCollection Date: 2023-01-01 DOI: 10.46471/gigabyte.103

Danielle C Wrenn, Devin M Drown

{"title":"Nanopore adaptive sampling enriches for antimicrobial resistance genes in microbial communities.","authors":"Danielle C Wrenn, Devin M Drown","doi":"10.46471/gigabyte.103","DOIUrl":"10.46471/gigabyte.103","url":null,"abstract":"Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.","PeriodicalId":73157,"journal":{"name":"GigaByte (Hong Kong, China)","volume":"2023 ","pages":"gigabyte103"},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10726737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138814643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0